The prevalence of lipid-related diseases in our society has generated a great need to advance our understanding of lipid metabolism. One major impediment to this has been the lack of live imaging studies undertaken in whole, living organisms. As a result, we lack a clear physiological understanding of where different dietary lipids accumulate subcellularly and how hormonal cues regulate the partitioning of lipids into different subcellular compartments. Insulin is known to regulate the expression and localization of many enzymes necessary for fatty acid (FA) metabolism; however, how insulin controls the partitioning of different chain length FAs (e.g. short, medium and long) into distinct subcellular compartments and metabolic pathways remains unknown. I hypothesize that insulin signaling directly mediates the subcellular partitioning of short, medium, and long chain FAs. To test this hypothesis I have created a feeding assay that utilizes fluorescent FA analogs to visualize FA metabolism in zebrafish larvae. Following a short feed, optically clear larvae exhibit intestinal, hepatic and pancreatic accumulation of the fluorescent FA analogs. Furthermore, when larvae are fed different chain length FAs, they partition into different subcellular compartments, with long and medium chain FAs entering lipid drops and chylomicrons and short chain FAs remaining in more aqueous environments. To investigate if insulin signaling controls subcellular FA partitioning, I will first feed long, medium and short chain FAs to larvae that lack insulin signaling and identify where they accumulate. I will then determine if insulin signaling responses are specific to FA chain length by making a transgenic zebrafish line that reports insulin signaling. This insulin reporter line will reveal tissue- and cell-specific responses to different FA chain length feeds and may uncover novel cellular responses to insulin signaling. These live imaging studies will allow me to directly elucidate the subcellular dynamics of FA partitioning and will ultimately lead to a better understanding of lipid-related diseases, such as diabetes and atherosclerosis.